CN116583468A

CN116583468A - System and method for order fulfillment sequencing and facility management

Info

Publication number: CN116583468A
Application number: CN202180081775.4A
Authority: CN
Inventors: 菲利普·J·普伊特; 弗雷德里克·D·赫拉彻; 马丁·托马斯; 杰夫·吉布森; 杰克·图恩斯特拉
Original assignee: Dematic Corp
Current assignee: Dematic Corp
Priority date: 2020-10-06
Filing date: 2021-10-06
Publication date: 2023-08-11
Also published as: WO2022074585A2; AU2021356752A1; WO2022074585A3; CA3198044A1; US20220106121A1; EP4225674A2

Abstract

Systems and methods for controlling an automated warehouse or order fulfillment facility are provided. The system comprises: a sequencing tower as a buffer for inbound items and shipping containers; and various pick/drop workstations coupled between the sequencing towers and an Automated Storage and Retrieval System (ASRS). The sequencing towers are adapted to receive, store and release newly formed shipping containers and inbound supplier bins. The pick/pour station acts as a hub between the ordering tower and the ASRS, wherein an operator at the pick/pour station picks the order items to a transport container to fulfill the order, or picks the inbound/supplier items to an inventory container to be stored in the ASRS. The system and method enables the sequencing towers and ASRS to synchronously release items to arrive at the workstation simultaneously, thereby optimizing the efficiency and throughput of the facility.

Description

System and method for order fulfillment sequencing and facility management

Technical Field

The present invention relates to order fulfillment systems and methods, and in particular, to systems and methods for shipping customer orders received via the internet, telephone, in-store terminal, or other order entry technology.

Background

Order fulfillment is a complex operation. Suppliers trucks deliver inventory cartons that must be removed from the truck and poured into a donor loading bin (donor tote) or other receptacle stored in an automated warehouse. The customer order is completed at a goods-to-person or robotic (GTP) station that receives the donor totes taken from the warehouse with inventory items for the order. If the donor totes are "pure SKUs," only one type of inventory item is stored in each tote or each tote section, and thus multiple donor totes are typically required to be taken to load an order. At the GTP station, the operator typically selects multiple orders at a time and must move between a donor tote and multiple order totes, each containing one or more orders. Each order may be a single item order placed in a single tote and sent to a packaging station or placed directly in a shipping container. The order may be a multi-item order that may be shipped directly in a container that is specially constructed for the cube volume of the items of the order using an automated carton forming machine (ACE) as known in the art. Some orders are shipped in plastic envelopes or bags, while other orders are shipped in bag-free condition, depending on customer needs.

All of the activities described above occur at different rates during different times. At some time of the year, the demand for certain items is greater, and other factors (such as discounts and promotions for related goods) may affect the demand for the items. In addition, operators operate at different speeds based on experience, regardless of their illness or other factors. This results in portions of the system operating at different loads. Some may overload work, while others "desire" work. Such inconsistencies are accommodated by the various buffers and other storage systems. Typically, to accommodate inefficiency, the system must be oversized. In the case of stock item out of stock, the order cannot be completed and therefore the order has to be deposited to wait for the missing item. Often, out-of-stock items may be on trucks, i.e., in yards, but not scheduled for unloading until later.

In view of the increasing popularity of electronic commerce and micro-fulfillment, the number and types of items ordered in this manner continue to expand rapidly. All of this adds complexity to the system, exacerbating all of the difficulties described above.

Disclosure of Invention

The present invention provides an integrated system and method for operating an order fulfillment facility, which may be in the form of an e-commerce fulfillment center, warehouse, micro-fulfillment center, or the like. The system includes a variety of subsystems that are substantially automated and versatile for carton forming, receiving, picking, pouring, integrating, and packaging. The subsystems include, but are not limited to, receiving, pouring, picking, packaging, yard control, and carton forming. The method synchronizes the ordering of the various subsystems to improve productivity and throughput and reduce downtime and material waste due to subsystem starvation. The system and method may synchronize the operation of the subsystems and may change the operational functions of the multipurpose subsystem, such as changing the pour-in workstation to a pick-up workstation and vice versa. The system includes a sequencing tower and storage system in the form of a multi-function elevator and an Automated Storage and Retrieval System (ASRS). The ordering tower is adapted to receive, store, and release shipping containers, inventory loading bins, and/or inbound containers (e.g., supplier bins). The sequencing tower serves as a hub for synchronizing various operations within the facility, and is in transport communication (e.g., connected by a conveyor) with the carton forming subsystem, receiving subsystem, pick/drop workstation, and transfer subsystem. The ASRS is in transport communication with the pick/drop station and the transfer subsystem. The pick/pour workstation serves as a hub between the ordering tower and the ASRS, where an operator picks order items to shipping containers or pick-up bins at the pick/pour workstation to fulfill orders, or picks inbound/supplier items to inventory containers for storage in the ASRS.

In one exemplary picking embodiment, the system and method controls and synchronizes the formation and subsequent release of various sized order containers with the release of inventory items (e.g., from an ASRS) to meet substantially simultaneously at the goods-to-person workstation to maximize carton formation, operator productivity, and subsystem throughput. In one exemplary pour embodiment, the system and method controls and synchronizes the release of inbound containers (e.g., from ASRS) and inventory containers (e.g., supplier cartons) of various sizes to meet substantially simultaneously as goods arrive at a manual station, thereby maximizing operator productivity, container utilization efficiency, and subsystem throughput. The ordering tower and Automatic Storage and Retrieval System (ASRS) enable synchronous ordering. The provided goods-to-person workstation design allows both pick and pour functions to occur interchangeably at a single workstation.

The system and method are particularly suited for streaming interleaving (e.g., allocation and optimization synchronization) of a particular item, order type, or order configuration. For example, the system and method can allocate and optimize the flow of single-line and multi-line orders during order fulfillment at a single workstation. The system and method also enables the distribution and optimization of the flow of items to be bagged (typically single items for single line orders) to be sent to the bagging system, while optimizing the utilization of the bagging system so that the bagging subsystem is not starved or overloaded. The system and method also enables the use of carton formers that are delivered to the sequencing towers to optimize the efficiency of each carton former and reduce the waste of material associated with oversized shipping containers.

The system and method provide a number of advantages over known systems, including: reducing the time line from order pick-up to customer delivery; the occupied area of the facility is reduced; redundant pick and drop workstations to flexibly handle receive/order volume imbalances; the workstations are spaced to enable social distance; relieving station starvation; the labor force requirement is reduced; efficiently transferring inventory between an ASRS machine and automated packaging; automatically processing "shortage" or open orders; the management of operation is simplified; sustainability is supported by minimizing material waste due to shipping carton size differences (e.g., unnecessarily oversized shipping cartons).

These and other objects, advantages, purposes and features of the present invention will become apparent upon reading the following description in conjunction with the accompanying drawings.

Drawings

FIG. 1 is a schematic illustration of a method for balancing and optimizing the flow of objects and containers in an automated warehouse facility in accordance with the present invention;

FIGS. 1A-1C are enlarged views of a method flow for the respective regions identified as 1A-1C in FIG. 1;

FIG. 2 is a schematic illustration of another method for balancing and optimizing the flow of objects and containers in an automated warehouse facility in accordance with the present invention;

FIGS. 2A-2I are enlarged views of a method flow for the corresponding region identified as 2A-2I in FIG. 2;

3A-3B are schematic illustrations of a method for sequencing and optimizing the flow of inventory items in an automated warehouse facility and the flow of shipping containers to a pick station in accordance with the present invention;

FIGS. 4A-4B are schematic illustrations of a method for sequencing and optimizing the flow of inbound items in an automated warehouse facility and the flow of inventory receptacles to an pour workstation (decant workstation) in accordance with the invention;

5A-5B are schematic illustrations of a method for guiding and optimizing the allocation of a plurality of items of the same type to different locations within an automated warehouse facility in accordance with the present invention;

FIG. 6 is a schematic diagram of a method for guiding and optimizing the allocation of different types of items commonly ordered together to the same location within an automated warehouse facility in accordance with the present invention;

7A-7B are schematic illustrations of a method for guiding and optimizing the pick-up and drop-off of inbound trailers at an automated warehouse facility, in accordance with the present invention;

FIG. 8 is a perspective view of a system for ordering order fulfillment subsystems in an order fulfillment facility according to one embodiment of the invention;

FIG. 9 is an elevation view of an exemplary sequencing column for the system of FIG. 8;

FIG. 10A is a perspective view of an exemplary sorter and exemplary sorting tower for the system of FIG. 8;

FIG. 10B is a plan view of the sorter and sorting tower of FIG. 10A;

FIG. 11A is a perspective view of an exemplary goods-to-person picking workstation for the system of FIG. 8;

FIG. 11B is a plan view of the goods-to-person picking workstation of FIG. 11A;

FIG. 12A is a perspective view of an exemplary goods-to-person pouring workstation for the system of FIG. 8; and

fig. 12B is a plan view of the goods-to-person pouring workstation of fig. 12A.

Detailed Description

Referring now to the drawings and the illustrative embodiments described therein, an order fulfillment and dumping ordering system 10 and methods 100, 200, 300, 400, 500, 600, 700 are provided for ordering and optimizing subsystems of an order fulfillment or warehouse facility 12. The system and method controls the flow and sequencing of inbound or vendor items, stored or inventory items, storage containers, and shipping containers. The method utilizes an electronic management system (such as computer system 13 with warehouse management software) to interconnect and synchronize facilities and operational functions of the entire interconnect subsystem, including shipment/receiving yard management, internal receiving, inventory and replenishment management, order management and fulfillment, guiding inbound item storage based on order history data, internal shipment functions, freight preparation and calculation, automation and mobile device management, and determining optimal locations for item picking if multiple workstations or facility sites/buildings are installed in the network. The method and system may be scaled to accommodate existing building size and/or facility throughput requirements. The method and system may be adapted for a variety of fulfillment facilities including warehouses, e-commerce order fulfillment facilities, micro-fulfillment facilities (e.g., grocery markets, retail), and on-line shopping-off-line pick-up facilities (on-line orders, pick-up directly by customers). As will be described below, a plurality of sequencing systems 10 may be deployed within the facility.

In the embodiment illustrated in fig. 8-12B, order fulfillment and dumping ordering system 10 is deployed in order fulfillment facility 12 and includes ordering tower 14 and Automatic Storage and Retrieval System (ASRS) 16. Wherein the ordering tower 14 functions as a hub between one or more pick/drop workstations 18 and a number of various facility subsystems. A computer system 13, such as a warehouse management system, monitors and controls the ordering tower 14, ASRS 16, and various subsystems to order and optimize the order fulfillment process within the facility 12 (see fig. 1-7B). The computer system 13 has various programs described in detail below, each of which is provided to perform a method for ordering and balancing order fulfillment processes to optimize throughput of the facility 12. Exemplary ASRS may be as described in commonly assigned us patent No. 8,974,168 published on month 10 of 2015, us patent No. 9,266,675 published on month 23 of 2016, and/or us patent No. 9,630,777 published on month 25 of 2017, each of which are incorporated herein by reference in their entirety. The pick/pour workstation 18 may be as described in commonly assigned U.S. patent application serial No. 16/829,134, 25 of 2020, 5, 6, 8,713,899, 9,604,781, 28, 2017, 3, 28, and/or 10,301,113, each of which is incorporated herein by reference in its entirety. Each pick/drop station 18 acts as a hub between the ordering tower 14 and the ASRS 16. The system 10 may include various optional or auxiliary subsystems such as a receiving subsystem, a shipping container or carton former subsystem, an automatic packaging subsystem, a centralized pouring subsystem, a manual pick subsystem, a manual packaging subsystem, a bag packaging subsystem, and a shipping subsystem, along with other intended subsystems, each of which is substantially automated. The method may be adapted to control ordering of trucking sites, such as which trucks in a lead site operator facility need to be received first, rather than in a first arrival order.

The system 10 is substantially automated and versatile and provides a number of benefits including reduced labor per order, reduced initial cost, and reduced building footprint for the facility. The computer system includes software that synchronizes various order fulfillment functions and flows, including sorting of shipping containers or pick-and-load bins of various sizes (when in pick-and-function) or vendor bins or item containers of various sizes (when in pour-in function) with inventory/donor containers from an automated storage and retrieval system at a person-to-person (GTP) or robot (GTR) workstation to maximize operator productivity and facility throughput. The computer system and corresponding software may interleave single line orders (i.e., single item orders) and multiple line orders (i.e., multiple item orders) during the execution of an order by a single workstation. Further benefits include: because of the discrete pick-up arrangement for the operator, the time line from order pick-up to customer delivery is shortened, and because the pick/drop-in workstation is closer to the output of the automated storage and retrieval system, the transport path is shortened; the building capacity is effectively utilized, so that the occupied area of facilities is reduced; the utility ratio of the equipment is minimized due to the multipurpose picking/pouring workstation, the multipurpose sorting tower, the general carton forming machine and the general automatic packaging station; optimizing/synchronizing ordering is made possible by the rich buffers in the ordering tower to accommodate the time challenges typically caused by lack of hardware availability; due to automated carton forming, dual transfer handling (inter-lane/short and long transfer) of inventory loading boxes in automated storage and retrieval lanes, and automated packaging, labor is optimized to reduce operator task starvation; and optimizing labor by utilizing a sequencing tower to temporarily store partially-loaded orders (i.e., shortage orders) until the remaining inventory is available at the pick-up station, reducing the actual operational requirements typically associated with handling and tracking "shortages".

The system 10 includes a sequencing tower 14, the sequencing tower 14 including an elevator or hoist arrangement 20, the elevator or hoist arrangement 20 servicing each of the rack levels 22 of the tower 14 to place or remove items or containers into or from each of the rack levels 22. The rack layer 22 is configured for storing containers (such as empty shipping cartons 24 and empty inventory/pick loading bins 26) and/or items (such as vendor bins 28). An exemplary elevator 20 may be that described in commonly assigned U.S. patent No. 9,555,967, published on month 31 of 2017, which is incorporated herein by reference in its entirety. The elevator includes an elevator platform 30 operably disposed on a vertical rod 32. The elevator platform 30 includes a plurality of drive rollers or drive conveyors for guiding articles or containers to the carrier layer 22 or from the carrier layer 22. The sorting tower 14 may include a buffer conveyor (such as an in-rack conveyor located at each rack level 22) configured to buffer articles or containers between storage locations in the respective rack level 22 and the elevator platform 30. The ordering tower 14 functions as a hub or buffer location to receive, hold and release the shipping cartons 24, pick-up loading bin 26, individual items and/or supplier bins 28 prior to release to the pick/pour workstation 18. The pick/dump station 18 is disposed adjacent the ordering tower 14 in a shipping transfer manner (e.g., connected by a conveyor or other type of conveyor system). Exemplary pick/pour workstations 18 may be described in commonly assigned U.S. patent application serial No. 16/829,134, 25 of 2020, 5, 6, 8,713,899, 9,604,781, 28, 2017, 3, 28, and 10,301,113, each of which are incorporated herein by reference in their entirety. It will be appreciated that the pick/drop station 18 is configured to operate interchangeably, either as an order fulfillment/pick workstation 18a (fig. 9, 12A and 12B) or as a drop workstation 18B (fig. 9, 11A and 11B), wherein in the case of the order fulfillment/pick workstation 18a, an operator retrieves items from the donor tote 34 (i.e., the tote containing items stored in the ASRS 16) and transfers items to the shipping carton 24 or pick tote 26, and in the case of the drop workstation 18B, an operator retrieves items from the supplier tote 28 and transfers items to the donor tote 34 for subsequent storage in the ASRS 16.

The sorting tower 14 of the illustrated embodiment is in transport communication with a sorting system or feed sorter 36 that receives inbound items and supplier bins 28 from other subsystems, such as a remote ASRS channel, receiving subsystem, centralized pouring subsystem, etc. The sorting tower 14 may be transported directly with the ASRS 16 via sorter 36. An exemplary sorter may be as described in commonly assigned U.S. patent No. 7086519, published 8/2006, which is incorporated herein by reference in its entirety. Sorter 36 has a variety of material handling functions including: directing the inbound supplier bins 28 into the sequencing tower 14; transferring donor totes 34 from a corresponding lane of ASRS 16 to other lanes of ASRS 16 that are not operatively connected to the corresponding lane by an inter-lane transfer system (this process is referred to as long transfer); directing donor loading bins 34 from other subsystems into sequencing column 14; and directing the empty donor tote 34 into the sequencing tower 14 or ASRS 16 as necessary. A shipping container or carton former 38 may be provided in communication with the sorter 36 or the sorting tower 14 and is provided for forming various desired sized shipping cartons 24 that are subsequently directed to the sorting tower 14 (fig. 8, 9 and 10B). The exemplary carton forming machine 38 may be a on-demand packaging machine such as that marketed and sold by Packsize International, inc (parker jersey international limited). It should also be appreciated that sorter 36 may be omitted such that sorting tower 14 primarily serves as a buffer for adjacent workstations 18.

As shown in fig. 8, multiple order fulfillment and dumping sequencing systems 10 may be deployed within a particular facility 12 or portion of a facility 12, and all systems 10 in the facility 12 controlled by a computer system 13. Referring to the embodiment shown in FIG. 8, an exemplary order fulfillment facility 12 includes three floors: namely, a first/base layer 41, a second layer 42, and a third layer 43 accessible to operators and autonomous vehicles. Sorter 36 serving each of systems 10 is disposed at base level 41, each system 10 in the facility includes workstation 18 configured to operate primarily as pick station 18a disposed at second level 42, and workstation 18 configured to operate primarily as drop station 18b disposed at third level 43, and sorter 36, pick station 18a, and drop station 18b are adjacent to sorting towers 14 and the respective floors and are in transit. The ordering tower 14 may be accessed at multiple levels to feed or output (pick, pour, etc.) the ordering tower. While the order fulfillment facility 12 of fig. 8 is configured with three floors, it should be appreciated that a desired configuration with additional or fewer floors (such as with more or fewer reorganizable workstations 18) may be selected as needed to meet throughput requirements in the facility. For example, any floor containing workstations 18 may be configured for any type of service, e.g., all workstation floors may be used for pick-up functions, all workstation floors may be used for pour-in functions, one floor may be used for pick-up functions, and two floors may be used for pour-in functions, etc. It will be appreciated that since the reorganizable nature of the workstation 18 is capable of operating as either a pick station 18a or an input station 18b, the workstation floors may operate differently at different times of the day as desired. The workstation 18 may be reconfigured substantially immediately once all previous functions are completed. Preferably, however, the workstation 18 is not changed too often, which may create inefficiencies in the system. The workstation 18 may include a trash conveyor or carryway 44, as shown in fig. 9 and 11A, which is particularly useful for removing trash or waste after an dumping operation, but may instead be unnecessary for a picking operation. The take-away channel 44 may be omitted if not required, but may be provided and controlled by the computer system 13 to operate only when required.

Referring to the embodiment shown in fig. 11A and 11B, the workstation 18 is depicted as being configured primarily as an docking station 18B. The docking station 18b is particularly suited for sequencing inbound items for placement into the donor tote 34 for subsequent storage in the ASRS 16. For example, inbound items or items in the form of a supplier tote 28 are released from the ordering tower 14 to the input station 18b, and a donor tote 34 (empty or partially loaded) is released from the ASRS 16 to the input station 18b, such that the supplier tote 28 and the donor tote 34 reach the input station 18b substantially simultaneously. The pour operator 40 unloads the supplier bins 28 and places inventory items into the donor load bins 34, preferably into a portion/compartment of the load bins 34, to maximize the capacity utilization of the load bins 34. The method 400 for optimizing capacity usage in the donor tote 34 will be described in further detail below. Once the donor tote 34 has received the requisite items, it is released from the transfer station 18b to the ASRS 16 for storage. Optimizing the ordering of inbound items using empty/partially empty donor totes 34 eliminates the need for upstream consolidation operations (typically, upstream consolidation operations are required to pour items and ensure proper subsequent placement into the ASRS 16). Preferably, each compartment in the donor tote is a "pure SKU" (i.e., if multiple inventory items are stored in a single compartment, then the items are identical to each other). The computer system 13 and program may control the size of the donor tote 34 released from the ASRS 16 or the size of the empty compartment of the tote 34 to meet but not greatly exceed the size required to pour the item in a manner that optimizes the volumetric usage of the donor tote 34. It will be appreciated that the poured items may be added to compartments already containing the items (preferably with the same SKU, i.e. a pure SKU), however, it is generally preferred to pour only into an empty container or empty compartment in a container, as this is more resource and time efficient.

With reference to the embodiment shown in fig. 12A and 12B, the workstation 18 is depicted as being configured primarily as a pick station 18a. The pick station 18a is particularly adapted to sort inventory items in empty shipping containers/cartons 24 or empty pick bins 26 from the sorting tower 14 and donor bins 34 transported from the ASRS 16 to the pick station 18a. For example, inventory items stored in the donor totes 34 are released from the ASRS 16 to the pick station 18a, and empty shipping cartons 24 are released from the ordering tower 14 to the pick station 18a, such that the empty cartons 24 and donor totes 34 arrive at the pick station 18a substantially simultaneously. The pick operator 46 transfers the desired items from the donor totes 34 to the shipping cartons 24, which once completed are then released downstream to another subsystem, such as a shipping subsystem. For another example, inventory items stored in the donor bins 34 are released from the ASRS 16 to the pick station 18a, and empty/partially empty pick bins 26 are released from the ordering tower 14 to the pick station 18a, such that the pick bins 26 and donor bins 34 arrive at the pick station 18a substantially simultaneously. The order picking operator 46 transfers the desired items from the donor loading bin 34 to the order picking loading bin 26, which, once completed, is then released downstream to another subsystem (such as another order picking station) to receive more order items, or to a packaging subsystem. Methods 100, 200, and 300 are provided for optimizing the ordering of shipping cartons 24 or empty inventory loading boxes 26 from ordering towers 14 with donor loading boxes 34 from ASRS 16, as will be discussed in further detail below. Once operator 46 retrieves the desired item from donor tote 34, tote 34 is released from docking station 18b back to ASRS 16 for storage.

As shown in fig. 12A, the pick station 18a may simultaneously receive and sort a plurality of empty shipping cartons 24 or pick bins 26 so that the pick operator 46 may contact each of them to allow the operator to pick multiple orders simultaneously. Multiple donor bins 34 may also be simultaneously released to pick station 18a so that operator 46 may remove items from multiple donor bins 34 to effectively fulfill orders. In a preferred embodiment, the computer system 13 and program orders the flow of cartons/pick bins and donor bins such that the first container closest to the operator 46 (as in the empty carton 24a shown in fig. 12A) is provided for the primary order being picked, and the first donor bin 34a includes the item to be picked into the first carton 24a for that primary order. In this manner, the operator 46 need only move a minimum distance to transfer articles from the donor loading bin to the desired carton/pick loading bin, thereby maximizing the throughput of the operator while minimizing operator fatigue. The operator 46 may pick items from the first donor tote 34a (or subsequent donor totes 34) to other shipping cartons/pick totes located at the pick station 18a, which maximizes operator time and throughput efficiency because the donor totes 34 are cycled if necessary.

The ordering tower 14 may be configured to receive and buffer oversized order items that are not suitable for pick-up bins or donor bins. Accordingly, the pick-up station 18a may be configured to receive and process oversized units that would otherwise not be suitable for loading bins. For example, the ordering tower 14 may buffer and then release oversized items and corresponding large empty shipping cartons to the pick station 18a, where the operator 46 may transfer the oversized items into the large shipping cartons. The computer system 13 and program may batch and sort a plurality of items embodied as a plurality of single item orders that require bagging at a downstream bagging subsystem. For example, a donor tote 34 containing items for a single item order from ASRS 16 is released to pick station 18a, and inventory tote 26 is released from ordering tower 14 to pick station 18a. Inventory loading boxes 26 are provided to receive a plurality of items that make up a plurality of single item orders. Once the inventory loading bin 26 is filled with items for a single item order, it is released from the pick station 18a to the downstream bagging subsystem where a bagging operator removes and individually bags each item from the inventory loading bin 26 to complete the order and then ships the bagged single item order.

Order fulfillment facility 12 may include a variety of optional or auxiliary subsystems in transportation communication with system 10 and controlled and monitored by computer system 13. Auxiliary subsystems include, but are not limited to: the automated shipping carton forming machine discussed above, the finishing and final packaging subsystem, the receiving subsystem, the centralized pouring subsystem, the manual packaging subsystem, the manual pick subsystem, the bag packaging subsystem discussed above, and the shipping subsystem.

The following provides a brief description of the above-described subsystems, however, it should be understood that the following description is not intended to limit the functionality and performance of the various subsystems within the facility 12. A plurality of automated carton formers (ACE) may be provided in each former subsystem adjacent to a respective sequencing tower 14. Each ACE may be configured to shape shipping cartons of a particular size (e.g., one ACE for large shipping cartons, one ACE for medium sized cartons, one ACE for small cartons, etc.). The former subsystem is in direct transport communication with the sorting tower 14 so that the formed shipping cartons can be introduced into the tower 14 and buffered without first passing through the sorter 36. The final packaging subsystem is provided downstream of the pick-up station 18 a. The final packaging subsystem may be fully automated and may include cushioning material, box sealing functions, and price inspection and labeling systems to identify, measure, mark, and guide shipping cartons. A receiving subsystem is provided upstream of the system 10 and is provided to introduce the incoming items to the facility 12, typically including retrieving the incoming items from a trailer or shipping container. The receiving system may include a telescoping discharge connected to a collector conveyor that cooperates to automatically receive incoming shipping items. The receiving subsystem may include a system for automatic shipment notification confirmation to verify that the received good matches the good that should be shipped. The receiving subsystem may include a system for automatically measuring and weighing received items or bins of items, as well as a system for creating a new SKU code for an item that is unique or new to the facility 12. An exemplary receiving subsystem is described in commonly owned and assigned U.S. patent application serial No. 16/575803, filed on date 19 at 9 and 2019, which is incorporated herein by reference in its entirety.

The computer system 13 and software may include placement logic (push logic) that optimizes the introduction, pouring and storage processes associated with entering an item or bin of items. The receiving system may provide benefits and functions including quality assurance and inbound Value Added Services (VAS). The centralized pouring subsystem may be located upstream 10 of the system to handle large scale pouring operations (e.g., the entire supplier bin may be poured and completely filled with donor loading bins 34, which donor loading bins 34 may then be directly input into the ASRS 16), special or fragile item pouring operations, oversized item or supplier bin pouring operations, and the like. The centralized pouring subsystem may be fully automated using a robotic pouring system, or may be at least partially manually operated by an operator. A manual pick subsystem may be provided upstream of the system 10 to handle pick operations for items that are not suitable for the hardware of the system 10 (e.g., items that are too large, too heavy, or of non-uniform shape that are difficult or impossible to handle by a storage shuttle). A manual pick subsystem may be necessary for inbound items received on pallets or shelves. The manual pick subsystem may be configured to direct items to different storage systems 12 within the facility 12, such as through a regional routing conveyor system. A manual packaging subsystem may be provided downstream of system 12 to handle standard packaging operations (operations that cannot be handled at the pouring station 18 b) and to handle and guide shipment of orders using the price check and labeling system. The bag packaging subsystem briefly discussed above may be provided downstream of the system 10 to transfer items from the pick-up totes 26 into shipping bags, which may be performed automatically. The completed order in the bag is transferred to a bulk container, such as gaylord, for delivery to a shipping supplier (e.g., an internal distribution network, UPS (united package delivery service), USPS (united states postal service), fedEx (federal express), DHL (DHL haven), etc.). The shipping subsystem may provide a final shipping function at the downstream end of the facility 12 to process the order as it is prepared to leave the facility 12, such as sorting the order cartons onto appropriate trailers. The shipping subsystem may include a telescoping trailer loader that facilitates sorting shipping cartons onto the trailer and may facilitate transfer of the lid, containing many orders, onto the trailer.

Referring to fig. 1-7B, the following methods 100, 200, 300, 400, 500, 600, and 700 are provided for synchronizing, balancing, and optimizing various order fulfillment flows in an order fulfillment facility 12. 1-1C, is provided for optimizing utilization of the pick station 18a, the input station 18b, the shipping carton former 38, the empty shipping cartons 24, the empty pick totes 26, and the donor totes 34 to operate the facility 12 in an efficient manner. The method 200, as shown in fig. 2-2I, is similar in many respects to the method 100, while additionally optimizing sub-flows in order fulfillment facilities, including determining order configurations (e.g., multi-item orders, single item orders, orders requiring shipping containers 24 and orders requiring bags, etc.), assigning orders to the system 10 and their respective ordering towers 14, assigning orders to pick stations 18a connected to the respective ordering towers 14, assigning inbound items and supplier bins 28 to the system 10 and their respective ordering towers 14, and assigning inbound items and supplier bins 28 to the input stations 18b connected to the respective ordering towers 14. 3A-3B, is provided for ordering and balancing the flow of objects (e.g., supplier bins 28, inbound items, etc.) and containers (e.g., shipping containers 24, inventory/pick loading bins or acceptors 26, etc.) from the ordering tower 14 with the flow of containers (e.g., donor loading bins 34) from the ASRS 16. Method 400, as shown in fig. 4A-4B, is provided for sequencing and optimizing the flow of inbound items (e.g., supplier bins 28) to the pouring station 18B and the flow of inventory receptacles (e.g., donor loading bins 34). The method 500, as shown in fig. 5A-5B, is provided for directing and optimizing the allocation of a plurality of items of the same type (such as items having the same SKU) to a plurality of different locations (e.g., different ASRS lanes) within an automated warehouse facility. Method 600, as shown in FIG. 6, is provided for directing and optimizing the allocation of different types of items, typically ordered together, to the same location within an automated warehouse facility. Method 700, as shown in fig. 7A-7B, is provided for guiding and optimizing the pick-up and drop-off of inbound trailers in an automated warehouse facility. Each of these methods will be discussed in further detail below.

Referring to fig. 1-1C, computer system 13 includes a program 48 that executes a method 100, method 100 including various steps for determining optimal use of resources in an order fulfillment facility, including: determining what items need to be input into the ASRS 16 by the pour operation, determining optimal utilization of space within the sequencing tower 14 as needed to reduce or eliminate starvation of downstream workstations (e.g., ensuring that sufficient shipping cartons 24 and pick-up loading bins 26 are available in the tower 14 to support the downstream pick-up station 18a, and that sufficient supplier bins 28 and inbound items are available in the tower to support the downstream pour station 18 b) to meet current and pending demands for these resources, and determining the pour rate of a particular pour station 18b based on production data for these pour stations 18 b. The program 48 includes a work time module 48a to determine an amount of work time, which is the productivity of a particular pick station 18a within the system 10 (e.g., fulfill one order per minute, fulfill two orders per minute, etc.). The program 48 includes a sequencing tower storage optimization module 48b that predicts the future/pending workflow for each workstation 18 to determine the optimal ratio of inbound item/supplier bins 28 to empty cartons 24/pick load bins 26 stored or buffered in the sequencing tower 14 to meet the current pour and pick demands 10 in the system 10. The program includes an pour rate module 48c to determine the pour rate of each pour station 18b in the system 12, the pour rate being for a particular pour station 18b within the system 10, e.g., one supplier bin per minute, two supplier bins per minute, etc.

Under the operation of module 48a, method 100 includes the step of assuming an amount of operating time based on database 50 of initial amounts of operating time (102). The program then calculates the amount of work time for each SKU in the pending order using the production data (104). The calculated amount of time of operation (104) is continuously performed to provide a real-time amount of time of operation for each SKU, which is updated and stored in the calculated amount of time of operation database 52.

The module 48b of the program 48 checks and calculates 106 the number of shipping containers required during the next user-defined period of time (e.g., ten minutes, one hour, one day, one week, etc.) (fig. 1A). A database or inventory 54 of pending orders is assigned to each pick-up station 18a and the database 54 is used to calculate the required shipping containers 106 and the calculated number of shipping containers required for each pick-up station 18a is stored in the database 56. Continuing from FIG. 1A to FIG. 1B, module 48B calculates 108 the number of containers in the form of vendor bins 28 required to be poured into each of the pouring stations 18B within the next user defined period of time and stores the calculated number in database 58 for each of the pouring stations 18B. Module 48b utilizes the operator pour rate (fig. 1A-1C) determined by module 48C and stored in database 60 in calculating 106 the number of containers that need to be poured. To determine the operator pour rate for each pour station 18b, module 48C assumes 110 a default or initial pour rate based on database 62 of initial pour rates and calculates 112 the pour rate for each pour station 18b based on the production data for station 18b (FIG. 1C). The calculation 112 of the pour rates is performed continuously to provide a real-time pour rate for each pour station 18b, and the calculated pour rates are stored in the database 60 of calculated operator pour rates. After calculating 106 the desired/to-be-processed shipping containers and calculating 108 the desired/to-be-processed containers for pouring, the module 48B calculates 114 an optimized ratio of inbound articles and supplier bins 28 to be stored in the ordering tower 14 to shipping cartons 24 and pick-up loading bins 26 for a given user-defined period of time (such as an instant, ten minute period, one hour period, etc.) (fig. 1A and 1B). The calculated ratio of order fulfillment resources (e.g., cartons 24, pick-load bins 26) to pour resources (e.g., supplier bins 28) for the sequencing tower is stored in a database 64 within the computer system for controlling and optimizing upstream and downstream flows in the facility 12.

A database 66 may be provided that contains the optimal configuration of workstations 18 within system 10. The database 66 provides how many pick stations 18a and how many drop stations 18b are needed for a particular ordering system 10 to optimize inventory inputs and order fulfillment outputs for the system 10. Database 66 may be controlled and updated by computer system 13 and program 48, however, it may be advantageous to obtain a database of optimized workstation configurations 66 from another subsystem or program, such as a program for determining an optimized arrangement and utilization of workforce. In some instances, not all of the workstations 18 may be required to be in operation at a given time, as provided by the optimized workstation configuration provided by the database 66.

Thus, the method 100 determines an optimal ratio of inbound items input to the ASRS 16 to shipping containers or pick-up bins to be buffered in the ordering tower 14 for order fulfillment to ensure that no starvation occurs at the downstream pick station 18a and the downstream drop station 18 b. The method 100 facilitates operation of the system 10 such that the system 10 operates at an optimized production level based on the order fulfillment requirements required. Generally, method 100 is combined with methods 200, 300, 400, 500, 600, and/or 700 to improve throughput and efficiency within facility 12. However, it should be understood that in some examples, the method 100 may be performed independently.

Referring to fig. 2-2I, computer system 13 includes a program 68 that executes a method 200, method 200 being similar in many respects to method 100 described above and also being provided for optimizing sub-flows within an order fulfillment facility, including: determining order configurations (e.g., multi-item orders, single item orders, orders requiring shipping containers 24, and orders requiring bags, etc.), assigning orders to sorting systems 10 and their respective sorting towers 14, assigning orders to pick stations 18a connected to respective sorting towers 14, assigning inbound items and supplier bins 28 to systems 10 and their respective sorting towers 14, and/or assigning inbound items and supplier bins 28 to an input station 18b connected to respective sorting towers 14. The program 68 includes a module 68a, the module 68a determining the appropriate configuration for packaging and shipping each order in the pending order list database 54 (FIG. 2A). For example, a to-be-processed order comprising multiple items or SKUs would require a box or other rigid container type shipping carton 24, a to-be-processed order for a single item may require a shipping bag, or a to-be-processed order for a single item may require a shipping carton 24, as determined by module 68 a. The program 68 also includes a drop-in optimization module (slotting optimization module) 68b, which drop-in optimization module 68b predicts future/pending workflows in the system 10 to determine the optimal destination for the supplier bins 28, shipping cartons 24, and pick loading bins 26 to be transported to a particular aisle in a desired pick station 18a, drop-in station 18b, or ASRS 16. Determining the best destination for an item is referred to as placing, wherein the item destination is predicted in a manner that selects the item destination for best efficiency for future order fulfillment processes.

The method 200 as executed by the program 68 includes a module 68a, the module 68a for determining a working time for pending orders and preparing a list of pending orders, the pending orders being categorized by configuration of the orders (fig. 2A). Module 68a assumes 202 a default amount of work rate time based on database 50 of initial or starting amounts of work time. Program 68 then uses the production data to calculate 204 the amount of work time for each pending order. The calculation 204 of the amount of work time may be performed continuously to provide a real-time amount of work time for each order. The module 68a splits 206 each pending order into several listings based on the shipping configuration required for the order, possible shipping configurations including: a multi-unit order to be packaged and shipped in shipping carton 24, a single unit order to be packaged and shipped in shipping carton 24, and a single unit order to be packaged and shipped in bags (referred to as plastic bags). Multiple items for a single unit of items may be batched into the pick box 26 so that the lot single item order may be delivered to a downstream bagging subsystem that may effectively handle the bagging process for the single item order. The module 68a then sorts 208 each of the pending orders based on their priority within the corresponding configuration category to prepare the database 70 of pending orders based on shipping configuration and priority.

Continuing from FIG. 2A to FIG. 2B, using the pending order list in database 70, method 200 includes selecting 210 from database 70 the multi-unit configuration order having the highest priority (FIG. 2B). A determination 212 is then made as to which ordering system 10 and corresponding ordering tower 14 and ASRS 16 channel currently has the maximum number of SKUs required to fulfill the multi-unit order. The method determines 214 if there are multiple ordering systems 10 in the facility 12 that contain the same number of required SKUs. If none, or in other words, one system 10 has more SKUs available for completing an order than any other system 10 in the facility, the program assigns 216 the order to the system 10 with the highest SKU available. If so, more than one system 10 contains the same number of SKUs for completing the order, and the program assigns 218 the order to the ranking system 10 having the lowest amount of work time assigned thereto (i.e., the ranking system 10 having the least amount of work to be processed is selected). Once the allocations 216 and 218 are completed, the multi-unit order allocation is stored in the ordering system allocation database 72. Concurrently with or subsequent to the multi-unit operation of steps 210-218, the program 68 then selects 220 from the database 70 the highest priority order for the single unit based on the desired shipping container configuration and determines 222 which ordering systems 10 contain SKUs required to fulfill the single unit order (fig. 2B). Continuing from FIG. 2B to FIG. 2C, the method then determines 224 if there is more than one ordering system 10 containing the required SKU for the single unit order. If none, or in other words, only one system 10 includes the required SKU, the program assigns 226 the single unit order to that system 10 that contains the required SKU. If so, more than one system contains the required SKU, and the program assigns 228 a single unit carton order to the ordering system 10 having the lowest shipping carton and pick loading bin total number assigned thereto (i.e., the ordering system 10 having the greatest remaining storage/buffer capacity). Once the allocations 226 and 228 are completed, the single units that require shipping carton allocations are stored in the ordering system allocation database 72.

Simultaneously with or subsequent to the multiple unit operations of steps 210-218 and the single unit operation of steps 220-228 requiring shipping of the cartons, the program 68 selects 230 from the database 70 the highest priority order based on the single unit requiring bag configuration and determines 232 which ordering systems 10 contain SKUs required to fulfill the single unit bag order (fig. 2C and 2D). The method then determines 234 if there is more than one ordering system 10 containing the required SKUs for a single unit bag order. If none, or in other words, only one system 10 includes the required SKU, the process assigns 236 a single unit bag order to that system 10 (fig. 2D) containing the required SKU. If so, more than one system contains the required SKU, and the program assigns 238 a single unit order to the ordering system 10 having the lowest amount of work time assigned thereto (i.e., the ordering system 10 having SKU and having the least amount of work to be processed is selected). Once the allocations 236 and 238 are completed, the single unit orders that require bag allocation are stored in the ordering system allocation database 72.

Continuing from FIG. 2D to FIG. 2E, at the same time or subsequent to steps 202-238, method 200 performed by program 68 selects 240 from database 72 the first ordering system 10 active in facility 12, then selects 242 the multi-unit order with the highest priority assigned to the selected ordering system 10, and determines 244 which lane of ASRS16 corresponding to the selected system 10 contains the largest number of required SKUs for fulfilling the selected multi-unit order. The program then determines 244 if there are two or more ASRS lanes containing the same high number of required SKUs to fulfill the order. If none, or in other words, only one lane contains the highest number of required SKUs, the program assigns 248 the selected multi-unit order to the pick station 18a corresponding to the lane of the ASRS16 having the highest number of required SKUs. If so, more than one aisle contains the same high number of required SKUs, and the program assigns 250 the selected multi-unit order to the pick station 18a having the lowest amount of work time assigned thereto (i.e., the pick station 18a having the least amount of work to be processed is selected). For example, in a system 10 that communicates directly with four ASRS lanes and the system 10 includes two pick stations 18a, each pick station 18a communicates directly with only two lanes of the four ASRS lanes, if one lane of the four lanes contains two SKUs required for a selected multiple unit order and each of the other four lanes contains only one SKU required for the order, then the program assigns the selected multiple unit order 248 to the pick station 18a corresponding to the ASRS lane containing the two required SKUs. As another example, in a system 10 that communicates directly with four ASRS lanes and the system 10 includes two pick stations 18a, each pick station 18a communicates directly with only two of the four ASRS lanes, if four SKUs are required for a multiple unit order and one of the two lanes corresponding to the first pick station 18a contains two required SKUs and one of the two lanes corresponding to the second pick station 18a contains two required SKUs, the program assigns 250 the selected multiple unit order to the pick station 18a with the lowest number of pending jobs. Once assignments 248 and 250 are completed, the multiple unit order assignments for each pick station 18a are stored in the pick station assignment database 82.

Concurrently with or subsequent to the multi-unit operation of steps 242-250, the program 68 selects 252 the single-unit order with the highest priority assigned to the selected ordering system 10 for which cartons need to be shipped and determines 254 which aisle of the ASRS 16 corresponding to the selected system 10 contains the required SKU to fulfill the selected single-unit carton order (fig. 2E). Continuing from FIG. 2E to FIG. 2F, the process then determines 256 whether the ASRS 16 corresponding to the selected system 10 has two or more lanes containing the required SKUs to fulfill the single unit carton order. If none, or in other words, if only one lane contains the desired SKU, the program assigns 258 the selected single unit carton order to the pick station 18a corresponding to the lane of the ASRS 16 having the desired SKU. If so, more than one aisle contains the required SKUs, and the program assigns 260 the selected single unit carton order to the sorting station 18a having the lowest shipping carton and pick-up loading bin total number assigned thereto (i.e., the sorting station 18a having the greatest remaining capacity for the shipping container fulfillment operations). For example, in a system 10 that communicates directly with four ASRS lanes and the system 10 includes two pick stations 18a, each pick station 18a communicates directly with only two lanes of the four ASRS lanes, if only one lane of the four lanes contains a selected SKU required for a single unit carton order, the program assigns 258 the selected order to the pick station 18a corresponding to the ASRS lane containing the required SKU. For another example, for a single unit carton order in the system 10 that communicates directly with four ASRS lanes, and the system 10 includes two pick stations 18a, each pick station 18a communicates directly with only two lanes of the four ASRS lanes, if one of the two lanes corresponding to the first pick station 18a contains the required SKU and one of the two lanes corresponding to the second pick station 18a contains the required SKU, the program assigns 260 the selected single unit carton order to the pick station 18a having the lowest number of shipping carton operations to be processed. Once the assignments 258 and 260 are completed, the single unit carton order assignments for each pick station 18a are stored in the pick station assignment database 82.

Simultaneously with or subsequent to the multiple unit operations of steps 242-250 and the single unit operation of steps 252-260 requiring shipping of cartons, the program 68 then selects 262 the single unit order with the highest priority assigned to the required bag of the selected ordering system 10 and determines 264 which lane of the ASRS 16 corresponding to the selected system 10 contains the required SKU to fulfill the selected single unit bag order (fig. 2F). Continuing from FIG. 2F to FIG. 2G, the program then determines 266 whether the ASRS 16 corresponding to the selected system 10 has two or more lanes containing the required SKUs to fulfill the single unit bag order. If none, or in other words, if only one lane contains the desired SKU, the program assigns 268 the selected single unit bag order to the pick station 18a corresponding to the lane of the ASRS 16 having the desired SKU. If so, more than one lane contains the required SKU, the program assigns 270 the selected single unit bag order to the pick station 18a having the lowest amount of work time assigned thereto (i.e., the pick station 18a having the least amount of work to be processed is selected). For example, in a system 10 that communicates directly with four ASRS lanes and the system 10 includes two pick stations 18a, each pick station 18a communicates directly with only two lanes of the four ASRS lanes, if only one lane of the four lanes contains a selected single unit bag order desired SKU, the program assigns 268 the selected order to the pick station 18a corresponding to the ASRS lane containing the desired SKU. For another example, for a single unit bag order in the system 10 that communicates directly with four ASRS lanes, and the system 10 includes two pick stations 18a, each pick station 18a communicates directly with only two lanes of the four ASRS lanes, if one of the two lanes corresponding to the first pick station 18a contains the required SKU and one of the two lanes corresponding to the second pick station 18a contains the required SKU, the program assigns 270 the selected single unit bag order to the pick station 18a with the lowest number of pending jobs. Once the assignments 268 and 270 are completed, the single unit bag order assignments for each pick station 18a are stored in the pick station assignment database 82. Method steps 210-240 and 242-270 are performed serially by computer system 13 and program 68 for each order to be processed, each of ordering systems 10 in facility 12, and each of pick stations 18a within ordering systems 10. Through continued operation, the method 200 provides the sequencing system 10 with an optimized and updated real-time sequencing to most effectively fulfill pending orders based on the historic and/or current productivity of the pick stations 18a in the facility 12. Thus, starvation (i.e., lack of work) at all pick stations 18a is reduced or eliminated when orders are to be fulfilled in the facility 12.

Based on the pick station job assignments, the program 68 creates 272 a list of shipping cartons 24 and empty pick-up loading cartons 26 required for the pending job assignments for each pick station 18a (fig. 2G). The program determines 274 the desired cartons 24 and bins 26 needed based on the user defined time period to ensure that the desired number of cartons and bins are buffered in the ordering tower 14 so that they are available at the pick station 18a when needed. The inventory of cartons 24 and load cartons 26 required is stored in a database 56, which database 56 may be accessed by various subsystems, such as a carton former subsystem.

Referring to fig. 2H-2I, program 68 includes a module 68b to perform a portion of method 200. The module 68b is provided for optimally distributing or placing inbound items into the lanes of the sequencing system 10, the input station 18b and the ASRS 16, and for creating a comprehensive list 80 of all inbound items in the facility (provider bins 28), empty shipping cartons 24, empty pick-up loading bins 26 on-time, expected order delivery time and expected order departure time. The module 68b performs the step of determining 276 which inbound items require an pour-in operation. Each unique item, whether inbound or already in the system, is indicated by a unique Stock Keeping Unit (SKU) identifier, and the inbound SKU is stored in a database 74 of automated shipping notices provided with the inbound item. A supplier box 28 (also referred to herein as a SKU box) containing a plurality of items may need to be poured and separated for distribution throughout various locations in the facility. For example, some inbound SKUs may not require an pour-in operation, such as large items, supplier bins that include only a single unit, and supplier bins with bulk packaging (which is intended to remain in bulk form for shipment to the end customer). Once the SKU that needs to be poured is determined at 276, the program 68 assumes 278 a default work rate timing number, such as from the start work time database 50. The amount of operating time for each received SKU that needs to be poured is then calculated 280 using the production data of the workstations 18 in the facility 12. The calculated amount of working time for each SKU is stored in the received SKU database 76. Each received supplier bin is then assigned 282 to the ordering system 10 within the facility 12 based on the most efficient placement determination, as discussed in more detail below with respect to methods 500 and 600. Once assigned to the sequencing system 10, the program 68 determines 284 the ideal docking station 18b within the system 10 to process the supplier bins (FIG. 2H). Continuing from fig. 2H to fig. 2I, program 68 determines 286 whether the desired docking station 18b selected has capacity to process the vendor bin. If not, the program 68 reassigns 288 the vendor bin to a different docking station 18b. The different docking station 18b may be selected as the next most desirable docking station 18b and/or the nearest docking station 18b with sufficient working capacity to handle the vendor bin. If the program determines 286 that the selected input station 18b does have sufficient working capacity, the program 68 then determines 290 if the ordering tower 14 connected to the selected input station 18b has sufficient capacity for the shipping container 24 and pick-up loading bin 26 as required for order fulfillment operations associated with the SKU of the inbound supplier bin. The program 68 accesses the database 56 of desired shipping cartons 24 and pick bins 26 for the pick station 18a in the selected ordering system (see fig. 2F-2I). If not, the ordering tower 14 associated with the selected drop station 18b does not have sufficient capacity, and the program 68 reassigns 292 the supplier bin to a different drop station 18b. As discussed above, the different docking station 18b may be selected as the next most desirable docking station 18b and/or the closest docking station 18b with sufficient working capacity for handling the supplier bins. If the program determines 290 that there is indeed sufficient capacity in the ordering tower 14 associated with the selected drop station 18b, the program 68 assigns 294 the selected supplier bin to the selected drop station 18b. The program 68 creates 296 a comprehensive list 80 of all inbound items (supplier bins 28), empty shipping cartons 24, empty pick-up loading bins 26 on-time, expected order delivery time, and expected order departure time within the facility 12. Based on the path of the ASRS 16 in direct communication with these pick stations 18a and drop stations 18b, a database 80 is created 296 for the job assignments for each pick station 18a and each drop station 18b. Database 80 is configured according to items stored in or to be stored in a particular aisle in ASRS 16.

Thus, the method 200 balances the ratio of the flow of the various articles in the facility 12, including the flow of shipping cartons relative to pick-up loading bins, the flow of single unit orders relative to multiple unit orders, the flow of bag orders relative to shipping carton orders, the flow of supplier bins relative to shipping cartons/pick-up loading bins, and the flow of shipping cartons of different sizes. The method 200 balances multiple item flows to maintain operational throughput of multiple downstream order fulfillment functions sharing the same hardware, including upstream supply resources (receiving subsystem, carton former subsystem, etc.) and/or downstream order fulfillment resources (ordering towers, ASRS, pick/drop workstations, etc.). The method provides dynamic, real-time mixing of inbound items (e.g., supplier bins) with order containers (e.g., empty shipping cartons and pick containers) to minimize starvation of any downstream functions. The desired ratio of the various flows is determined based on user-defined factors (e.g., business/customer decisions whether a particular SKU is in a high demand state due to a holiday, or whether a retail store is promoting a particular SKU, etc.).

Balancing single unit orders versus multiple unit orders is particularly beneficial because many single unit orders can bypass the ordering tower and/or the carton former system, thereby controlling the rate of consumption of shipping cartons and system 10. Balancing of the bagged single unit order relative to the carton packaging single unit order is particularly beneficial because the items to be packaged in the bags are typically not handled by the pick operator 46, but are otherwise handled in the facility at a different location downstream of the pick station 18 a. The pick operator 46 typically batches a number of items for a single unit bag order into one container (e.g., pick box 26) to be sent to a bagging system where each item will be individually bagged. The method 200 creates a steady flow of items to the bagging subsystem, which controls a large influx to the bagging subsystem.

Balancing shipping the differences in carton sizes is particularly beneficial because excessive consumption of containers of one size may over-use one carton forming machine while limiting the contribution of other carton forming machines, which would reduce overall efficiency, otherwise all of the carton forming machines may be used in the most efficient manner. The method 200 balances orders to be picked in a manner that effectively utilizes the carton forming machine associated with the ordering tower. For example, the carton former subsystem may include three carton formers dedicated to the sequencing tower 14, wherein each carton former produces a different sized container. The method 200 desirably balances the orders within the system 10 such that one third of the shipping cartons required in the system 10 come from each carton former. Thus, balancing shipping carton sizes minimizes cardboard consumption and maximizes throughput.

Generally, method 200 is combined with methods 100, 300, 400, 500, 600, and/or 700 to improve efficiency and throughput within facility 12. However, it should be understood that in some examples, the method 200 may be performed independently.

Referring to fig. 3A-3B, computer system 13 includes a program 84. Program 84 executes method 300, method 300 being provided for ordering and balancing the flow of objects to order fulfillment/pick station 18a in facility 12. The method 300 orders and balances the flow of containers (e.g., shipping containers 24, inventory/pick-up loading bins or containers 26, etc.) from the ordering tower 14 with the flow of containers (e.g., donor loading bins 34) from the ASRS 16. The routine 84 is continuously executed to balance the flow at each pick-up station 18a in the facility 12. The method 300 includes selecting 302 a next pending order in the pending order database 54 and using the database 86 of items stored in the ASRS 16 to determine 304 whether the inventory required for the pending order is available in the ordering system 12. If the desired item is not available in ASRS 16, the selected order is placed back 306 in the pending order database and program 84 selects 302 the next pending order. If the desired item is available in ASRS 16, program 84 selects 308 a target or optimized pick station 18a to send the pending order for time and resource efficiency. For example, the pending order may be directed to a pick station 18a located adjacent to the aisle of the ASRS 16 containing most or all of the inventory items required for the pending order.

The program 84 then determines 310 whether the target pick station 18a is available to process the pending order. If the target pick station is not available to process the pending order, the program 84 places 306 the order back into the pending order database 54 and the program 84 selects 302 the next pending order. If the target pick station is available to process the pending order, the program 84 instructs 312 the system 10 to direct all inventory items (via the donor tote 34) to be transported to one of the lanes of the ASRS 16 corresponding to the target pick station 18 a. This may be accomplished by an inter-lane transfer system (such as described in U.S. patent No. 9,452,886 published by 2016, 9, 27, incorporated herein by reference in its entirety) from a nearby lane of the ASRS 16 connected to the target ASRS lane by an inter-lane transfer, or by a long transfer as described above, in which a donor loading bin 34 with the desired items is transferred from a far ASRS lane to the target ASRS lane via sorter 36. Program 84 then determines 314 if all of the required donor load bins 34 are present in the target ASRS channel of sequencing system 10. If not all donor totes 34 are available at the target aisle, then routine 84 delays 316 further action until the donor totes 34 reach the target ASRS aisle. If all donor totes are available at the target aisle, the program 84 commands 318 the appropriate shipping/staging container, such as the shipping carton 24 or the pick-up tote 26 (such as from the carton former 38), to be input to the ordering tower 14.

The program then determines 320 whether the desired shipping carton 24 or loading box 26 is present in the ordering tower 14. If the desired shipping carton or pick box is not present in the ordering tower 14, the program 84 delays 322 further action until the desired shipping carton or pick box is present in the ordering tower 14. If the desired shipping cartons or pick-up bins are present in the ordering tower 14, the program 84 instructs 324ASRS 16 to release all of the desired donor bins 34 for delivery to the target pick-up station 18a and instructs 326 the shipping cartons 24 or pick-up bins 26 to be delivered to the target pick-up station 18a. The commands 324 and 326 will be communicated to the pick station 18a substantially simultaneously so that the pick operator 46 may pick items from the desired donor tote 34 into the desired shipping carton 24 or pick tote 26 with little or no delay or starvation. Once at the pick-up station 18a, the operator 46 is instructed which donor tote 34 to pick from, the number of items to pick from that tote 34, and the shipping/staging container (shipping/staging container) into which the items are to be placed. Once the pick from the donor tote 34 is completed, the tote is returned to the ASRS 16 for storage, which may then be used for future order fulfillment or pouring operations. Once order fulfillment for the shipping carton 24 or pick box 26 is completed, the shipping/escrow container is released to the downstream subsystem, such as routed to the packaging subsystem for automatic billing, sealing, weighing, and shipping price pricing and labeling by the price checking and labeling system, as required by the next required process. Once packaging is complete, the order container proceeds from the packaging subsystem to the shipping subsystem.

Generally, method 300 is combined with methods 100, 200, 400, 500, 600, and/or 700 to improve efficiency and throughput within facility 12. However, it should be understood that in some examples, the method 300 may be performed independently.

Referring to fig. 4A-4B, computer system 13 includes a program 88. Program 88 executes a placement logic algorithm that performs method 400. The method 400 is used to pour and allocate each item in an inbound container (e.g., the vendor box 28) to an ASRS aisle and to a minimum available cubic inventory container or minimum compartment in the available containers of sufficient size to store the particular poured item. Program 88 manages the allocation of inventory receptacles (i.e., donor totes 34) to ASRS 16, inter-lane transfers occurring within lanes of ASRS 16, and long-distance transfers occurring outside of the lanes (e.g., by sorter 36). Program 88 controls ASRS 16 to sequentially send donor load bins 34 to arrive simultaneously with the corresponding inbound supplier bins 28. Preferably, each donor tote 34 and/or compartment within the donor tote is a pure SKU (i.e., includes only the same item if it contains more than one item).

Program 88 and placement logic are configured to simultaneously request inbound containers (e.g., vendor bins 28) from sequencing tower 14 and corresponding inventory containers (e.g., donor bins 34) from ASRS16, wherein donor bins 34 are selected based on whether donor bins 34 have an effective size for the poured items. In other words, if the donor tote 34 has a compartment available that is large enough but not too large for the item to be poured, then the donor tote 34 is selected from the ASRS 16. Matching inbound items to available storage containers/compartments having an effective size optimizes storage density within facility 12. Underutilized storage density can increase the required footprint of the facility. For example, it is inefficient to store items requiring only one eighth (1/8) of the compartment of the donor tote 34 into one half (1/2) of the compartment of the donor tote 34. For another example, program 88 and placement logic may determine that storing three items with the same SKU into a compartment that is one-half (1/2) of the donor tote 34 is an inefficient space use, while placing each of the three items into a separate compartment that is each one-eighth (1/8) of the donor tote 34 (i.e., 3*1/8=3/8<1/2) is a more efficient space use. The individual compartments may be located in the same tote 34, however, items may also be distributed among available compartments in multiple different totes 34, which increases the variety of storage locations for multiple identical SKUs throughout the ASRS 16. Placement logic increases storage utilization per donor tote 34, increases storage density/utilization of ASRS16, and increases SKU storage diversity. Placement logic preferably reduces lane-to-lane transfer (lane-to-lane or long lane transfer) of inventory receptacles and/or reduces the distance that receptacles travel during transfer. In other words, when needed at the pick station 18a for order fulfillment, the distribution of multiple identical SKUs among multiple donor totes results in less movement/transfer and shorter distance movement required to move items to the target aisle of the ASRS 16. Once the inbound containers are identified, the program 88 assigns the inbound containers to ASRS lanes based on the current inventory distribution in the facility, the historical SKU consumption, and the cumulative availability of the inbound containers.

The following is a detailed description of the steps of the method 400 as shown in fig. 4A-4B. The program 88 selects the next inbound supplier pod 28 from the inbound supplier pod inventory database 76 and assigns 402 the supplier pod to the inbound 18b via the corresponding ordering tower 14. The allocation 402 is performed by the program 88 by placing the database 90 with SKUs. SKU placement database 90 contains recommended or optimized SKU placement selections based on pending orders and hardware utilization within device 12. As discussed in more detail below with respect to methods 500 and 600, placement selections in placement database 90 may be created based on historical production and order data, user-defined production and order data, and/or current production and order data. The program 88 then determines 404 whether there is capacity in the selected ordering tower 14 to handle the pour operation for the selected supplier bin. If the tower 14 has no capacity, the process recirculates or delays 406 the supplier pod and allocates 402 the next supplier pod to the pour station 18b. If it is determined 404 that the selected ordering tower does have capacity, the program requests 408 that empty inventory loaders 34 from the ASRS 16 be transported to the docking station 18b. The routine determines 410 whether all items for the pour operation are present in the sequencing column 14, e.g., the routine determines whether all supplier bins required to fill an empty donor tote are present in the column 14. If not, the program 88 delays 412 the operation and performs a different pour-in operation. If all of the items are present in the sorting tower 14, the program releases 414 all of the desired items from the tower 14 to the pour station 18b. Preferably, the claim 408 and subsequent transport of the empty totes 34 to the pick station is performed substantially simultaneously with the release 414 of the items from the ordering tower 14, such that the empty totes 34 arrive at the pour station 18b with all of the pour items. The operator (human or robot) then pours 416 the desired item into the donor tote 34, which is stored in the ASRS 16 once the pouring operation is complete. The operator is instructed to pick from which supplier bin (when multiple supplier bins are present at the infeed station), and to place these units into which inventory loading bin or bin compartment. Once the donor totes are stored in ASRS 16, inventory database 86 of items stored in ASRS 16 is updated to reflect the current inventory.

Generally, method 400 is combined with methods 100, 200, 300, 500, 600, and/or 700 to improve efficiency and throughput within a facility. However, it should be understood that in some examples, the method 400 may be performed independently.

Referring to fig. 5A-5B, computer system 13 includes a program 92. Program 92 executes a place logic algorithm and performs method 500. For example, the method 500 is used to guide and optimize the allocation of multiple items of the same type (e.g., items having the same SKU (otherwise referred to as "SKU instances") to various different locations within an automated warehouse facility, such as to different ASRS lanes. Program 92 allocates SKU instances or a number of single SKUs among the plurality of donor totes 34 so that each SKU instance may be spread throughout facility 12. Program 92 may redirect the totes 34 containing SKU instances of the SKU throughout the facility (e.g., to a different location or subsystem) based on the predicted consumption rate of the SKU. Doing so increases the number of SKU instances and donor totes 34 containing the SKU so that the SKU can be transported to multiple workstations at the same time if desired, and also reduces reliance on shared resources between the workstations. For pour operations, the method 500 generally assigns SKUs to empty containers/container compartments. However, the method 500 may be used to fill containers/compartments, otherwise known as inventory saturation, wherein the volume of the donor tote is fully utilized.

The following is a detailed description of the steps of the method 500 as shown in fig. 5A-5B. The program 92 examines 502 characteristics of each inbound SKU, such as the inbound SKU received in the receiving subsystem, to determine a target placement area that is ideal for the size and/or requirements of the SKU. The check 502 is performed in comparison to the SKU master database 94 and the recommended target placement area is stored in the recommended SKU placement database. The target placement area may be a storage location within the ASRS 16 or may be a different subsystem for specifically handling certain SKUs. For example, a large item SKU (such as a bag of dog food or a set of golf clubs) may be directed to the manual pouring subsystem because the hardware in the automated ordering system 10 may not be able to handle the SKU. For each inbound SKU, the program predicts 504 a demand requirement for that SKU during a future user-defined period (e.g., ten minutes, one hour, twenty-four hours, etc.) based on the historical demand data for that SKU stored in the historical demand database 96. The predicted demand requirements for each inbound SKU are stored in a predicted demand database 98.

The program application 506 requests the predicted demand for each SKU and user-defined promotional inputs provided by the user through the promotional input database 116 to create a prediction of the demand for that SKU based on the promotional inputs stored in the database 118. For example, a user may promote a frozen turkey during a holiday season and user-defined promotion data will be applied 506 by the program 92 to predict the need for that turkey SKU during the promotion and/or during the user-defined period. The program 92 calculates 508 the number of SKU instances of the SKU required during the user-defined period from the productivity 52 for the pick-up station 18a in the facility 12 (see exemplary discussion regarding the calculation of the amount of work time 52 (e.g., productivity) performed for the method 100 as described above) and the predicted promotional demand 118. The number of SKU instances of that SKU required is stored in database 122 and represents the number of SKU instances or SKU copies that need to be distributed throughout facility 12 to ensure that the predicted demand will be met during the user-defined promotional period. Program 92 continuously executes method 500 to replenish the SKU as it is consumed or depleted so that inventory of SKUs is desirably always available to meet the predicted demand.

Generally, method 500 is combined with methods 100, 200, 300, 400, 600, and/or 700 to improve efficiency and throughput within facility 12. However, it should be understood that in some examples, the method 500 may be performed independently.

Referring to fig. 6, computer system 13 includes a program 124 that executes a placement logic algorithm. The placement logic algorithm performs the method 600. The method 600 is used to guide and optimize the distribution of different types of items, typically ordered together, to the same location within an automated warehouse facility. The method 600 utilizes historical consumer purchase patterns to create groups or families of SKUs that are typically ordered together. For example, a family of SKUs that can be ordered together includes hammers ordered with nails, toothbrushes ordered with toothpaste, and the like. Program 124 utilizes the historical SKU data from database 96 to create 602 a database of SKU groups 126 determined based on patterns found in the historical SKU order data 96. The number of SKU instances 122 in facility 12 is used by program 124 with SKU group 126 to create 604 a SKU placement plan 128 to guide inbound SKUs based on the required SKU instances and group patterns. SKU instance 122 can be provided by method 500 discussed above, or by another process or by user-defined input. Generally, method 600 is combined with methods 100, 200, 300, 400, 500, and/or 700 to improve efficiency and throughput within facility 12. However, it should be understood that in some examples, the method 600 may be performed independently.

Referring to fig. 7A-7B, computer system 13 includes a program 130. Program 130 performs method 700. Method 700 is for guiding and optimizing the signing up and unloading of inbound transport vehicles/trailers at an automated warehouse facility. As discussed herein, an inbound or receiving trailer is also referred to as a signoff. Program 130 orders and assigns vehicles to appropriate facility gates to support order fulfillment facility operations. Program 130 prioritizes the unreceived inventory (i.e., inventory that has not entered the facility but is otherwise on site) based on current order requirements to optimize ordering of vehicles and their allocation to appropriate facility gates for offloading inventory. Program 130 also prioritizes and ranks outbound vehicles by assigning to appropriate utility gates for loading and temporary storage for future departure. For warehoused items, the method 700 optimizes the endorsement of the inbound SKU to replenish the under-inventory or depleted SKU within the facility 12. Such optimization is beneficial in reducing the shortage of orders that are not delivered due to under-stock. The method 700 improves the efficiency of inventory planning, which is particularly beneficial during the occurrence of inventory peaks, such as during holiday seasons. For outbound items, method 700 optimizes the efficiency for staging the vehicle, reduces door-to-door movement of the vehicle due to upstream errors, and improves the efficiency of the vehicle driver by providing enough time and space to avoid other vehicles from operating. The method 700 prioritizes the trailers based on the SKUs contained in the trailers and the needs of those SKUs within the facility, rather than based on the order of arrival of the trailers. In other words, trailers with unneeded SKUs are not introduced into the doors based on whether they arrive first at the facility, but rather on which of the trailers in the field has the highest number of SKUs needed or the highest priority SKUs needed in the facility 12. The method 700 may also be used to guide trailers between the various buildings that make up a single interconnected facility 12, and may also be used to operate multiple facilities that are not physically or operationally connected to each other.

The following is a detailed description of the steps of the method 700 as shown in fig. 7A and 7B. Program 130 utilizes historical SKU order information 96 to predict 702 demand for SKUs within facility 12 during a future user-defined period of time in a manner similar to that described above with respect to step 504 of method 500. For example, the user-defined time period may be selected by the user as desired, such as during the next hour time period, during the next twenty-four hour time period, during the entire promotional time period, during seasonal shopping periods, and so forth. The predicted SKU requirements are stored in database 98. Similar to that described above with respect to step 506 of method 500, program 130 applies 704 the predicted demand requirements for each SKU and the user-defined promotional input from database 116 to create a prediction of demand for each SKU based on the promotional input, which is then stored in database 118. Using the current demand or pending order list 54, a calculated larger SKU demand database 138 is created by comparing 706 the predicted demand 118 for the SKU with the current demand from the pending order list 54, where the larger these numbers represent the larger the calculated SKU demand. The program then compares the calculated larger SKU requirements to the inventory within the facilities in database 140 to create 708 a shortfall inventory 142. The inventory stored in database 140 may be the same as the inventory in ASRS 16 presented in database 86, however it may also include additional inventory within facility 12 outside ASRS 16, such as additional inventory in a manual pour subsystem, in sequencing tower 14, in a receive subsystem, etc. The shortage list 142 presents SKUs that need to be replenished to meet SKU requirements within the facility, and the shortage list 142 is then used to reorder the trailers to meet the requirements as effectively as possible based on SKUs available on site trailers.

Program 130 then compares the shortfall inventory 142 to SKUs currently on the on-site pending trailers 144 at facility 12 to create 710 an on-site trailer inventory 146 containing the shortfall SKUs. SKUs on the pending trailers 144 are known by Automated Shipping Notices (ASNs) (e.g., electronic bill of lading). Based on the pending trailers 144 and the trailer inventory containing the SKUs 146 that are in shortage, the program 130 reorders 712 the pick/trailers (if they are mobile) on the pending inventory 144 to prioritize trailers containing SKUs on the shortage inventory. In some cases, the trailer may not be movable, such as if it is already at the receiving door or is otherwise unsuitable for movement. The reordered checkouts/trailers inventory may be stored in a different database 148 or may be incorporated into database 144 such that method 700 continuously optimizes inbound trailer flow. Thus, the method 700 reorders the contents of the field trailers based thereon to accommodate inventory shortages within the facility 12.

Generally, method 700 is combined with methods 100, 200, 300, 400, 500, and/or 600 to improve efficiency and throughput within facility 12. However, it should be understood that in some examples, method 700 may be performed independently.

As described herein, the disclosures of the systems and methods disclosed in the following commonly assigned documents are incorporated herein by reference in their entirety: U.S. patent application Ser. No. 16/575,803, U.S. patent application Ser. No. 16/829,134, U.S. patent application Ser. No. 16/8232,134, U.S. patent application Ser. No. 25,, U.S. patent No. 10,062,046 to Ogden entitled "DYNAMIC RATE MATCHING FOR MATERIAL HANDLING" published 28 at 8, 2018, and U.S. patent No. 10,301,113 to Stevens et al entitled "PICKING STATION WITH AUTOMATED WAREHOUSE" published 28 at 5, 2019.

Thus, the order fulfillment and dumping ordering system 10 and methods 100, 200, 300, 400, 500, 600 are provided for ordering and optimizing subsystems of order fulfillment or warehouse facilities 12 to improve efficiency of facility hardware and labor, thereby improving throughput. The system and method control the flow and sequencing of inbound items as they are transported to a facility and the inbound items are poured for storage. The system and method control the flow and ordering of storage containers and order fulfillment containers for order fulfillment processes. The method uses an electronic management system to interconnect and synchronize the entire facility and its subsystems and workforce. The method may be adapted to optimize shipment/receiving yard, internal receipt, inventory, order fulfillment, placement based on order history data, and ordering and control of internal shipments, among other desired functions and flows. The method and system may be scaled to accommodate existing building size and/or facility throughput requirements. The method and system may be adapted for a variety of fulfillment facilities including warehouses, e-commerce order fulfillment facilities, micro-fulfillment facilities (e.g., grocery markets, retail), and on-line shopping-off-line pick-up facilities (e.g., online orders, pick-up directly by customers). Multiple sequencing systems 10 may be deployed within a facility and controlled by the same electronic management system.

Alterations and modifications of the specifically described embodiments may be carried out without departing from the principles of the invention, which is intended to be limited only by the scope of the appended claims as interpreted according to the principles of patent law, including the doctrine of equivalents.

Claims

1. An automated warehouse management system, comprising:

a computer system configured to control the automated warehouse management system;

an automatic storage and retrieval system;

a plurality of workstations in transport communication with the automated storage and retrieval system, the workstations configured to perform at least one operation selected from an order fulfillment operation and an dumping operation; and

a sequencing tower in transportation communication with the automated storage and retrieval system and the plurality of workstations, the sequencing tower configured to buffer items until instructed by the computer system to release items to one of the plurality of workstations;

the computer system is configured to sort inbound and outbound items between the sorting tower, the automated storage and retrieval system, and the plurality of workstations based on at least one selected from pending orders and predicted demand, wherein the computer system releases items from the sorting tower and from the automated storage and retrieval system in a manner that allows items to arrive at a respective one of the plurality of workstations at the same time.

2. A warehouse management system as claimed in claim 1, wherein the ordering tower includes an elevator system, a plurality of storage locations, and a plurality of buffer conveyors for conveying items into and out of the ordering tower.

3. A method for balancing resources within an automated warehouse facility, the method comprising:

calculating, using a warehouse management system, a production rate for each item in the pending order to be fulfilled within the facility;

using the warehouse management system, calculating a number of required order fulfillment containers to be required during the defined period of time based on the inventory of pending orders;

calculating, using a warehouse management system, a quantity of inbound items that will be required to meet inventory requirements during a defined period of time to supply the pending orders;

calculating, using a warehouse management system, an pour rate for each of a plurality of pour workstations in a facility;

the warehouse management system is used to calculate the optimal ratio of inbound items and order fulfillment containers to be directed to each of the dump workstations to supply pending orders.

4. A method as claimed in claim 3, wherein the inbound items and order containers are stored in the sorting buffer until the warehouse management system releases the respective item or container to one of the plurality of dumping stations in communication with the sorting buffer.

5. The method of claim 4, wherein the sorting buffer comprises a sorting tower comprising an elevator system, a plurality of storage locations, and a plurality of buffer conveyors for transporting items into and out of the sorting tower.

6. A method for balancing resources within an automated warehouse facility and assigning workflows to workstations within the facility, the method comprising:

calculating a productivity rate for each pending order selected from a database of pending orders using a warehouse management system;

sorting individual ones of the pending orders into a plurality of sub-listings based on a shipping configuration required for each order;

for each highest priority order in each sub-inventory, assigning each selected order to one of a plurality of ordering systems within the facility, wherein each ordering system includes an ordering tower and a plurality of pour and order fulfillment workstations in transit with a particular aisle of an automated storage and retrieval system configured to store and retrieve items within the facility, the assigning each selected order to an ordering system being performed based on a most efficient resource allocation determined based on a relative positioning between resources of the ordering system and locations of desired items stored in the automated storage and retrieval system;

For each ordering system within the facility, assigning each order assigned to the respective ordering system to one of a plurality of order fulfillment and dumping stations within the ordering system, wherein each order fulfillment and dumping station is adapted to perform any one of the order fulfillment operations and dumping operations, said assigning each selected order to a station being performed based on a most efficient resource allocation determined based on a relative positioning between the station of the ordering system and a location of a desired item stored in the automated storage and retrieval system;

buffering the required shipping containers for each order assigned to the ordering tower; and is also provided with

Wherein when the desired shipping containers and all desired items for the selected order are available at the respective ordering towers and automated storage and retrieval systems, all desired items are released so that they arrive at the selected workstation at the same time.

7. The method of claim 6 wherein the sub-listing orders comprise an order selected from the group consisting of a multi-unit order, a single-unit order requiring shipping of the carton, and a single-unit order requiring shipping of the bag.

8. The method of claim 6, further comprising assigning an inbound container to a preferred workstation of the plurality of workstations within the ordering system, the assigning the inbound container being performed based on a most efficient resource allocation determined based on a capacity of the selected workstation and a preferred storage location for the item within the automated storage and retrieval system according to future order fulfillment requirements for the item in the inbound container.

9. A method for ordering and balancing flow of containers for order fulfillment operations within an automated warehouse facility, the method comprising:

determining, using a computer system configured to control an automated warehouse facility, whether inventory items required for a selected pending order are available in an automated storage and retrieval system within the facility;

wherein if the inventory item is not available in the automated storage and retrieval system, a different order to be processed is selected for processing;

wherein if the inventory items are available in an automated storage and retrieval system, the selected pending orders are assigned to a sequencing system in transit with the automated storage and retrieval system;

Determining, using a computer system, whether a shipping container required for the selected pending order is available in a sequencing buffer of a sequencing system;

wherein if the shipping container is not available in the sorting buffer, a different pending order is selected for processing;

wherein if the shipping containers are available in a sequencing buffer, the selected pending orders are assigned to order fulfillment workstations in communication with the sequencing buffer; and

the shipping containers are released from the sequencing buffer to the selected workstation and the inventory items are released from the automated storage and retrieval system to the selected workstation such that the shipping containers and inventory items arrive at the assigned workstation simultaneously.

10. A method of pouring and dispensing each item in an inbound container to a location within an automated warehouse facility, the method comprising:

assigning inbound containers to a sequencing system within the facility using a computer system configured to control an automated warehouse facility, the assigning inbound containers being performed based on optimal locations of items in the inbound containers in an automated storage and retrieval system within the facility;

buffering the inbound containers in a sequencing buffer of a sequencing system;

Releasing inventory receptacles from the automated storage and retrieval system within the facility for transport to an dumping workstation in transport communication with each of the automated storage and retrieval system and the sequencing buffer of the sequencing system; and

releasing inbound containers from the sequencing buffer to the dumping workstation;

wherein said releasing the inventory container and said releasing the inbound container are performed by a computer system such that the inventory container and the inbound container arrive at the pouring station simultaneously.

11. A method for distributing a plurality of items of a same type to a plurality of different locations within an automated warehouse facility, the method comprising:

determining, using a computer system configured to control an automated warehouse facility, a target storage location for an inbound item based on a size of the inbound item and a demand for the inbound item;

predicting, using a computer system, demand requirements for the inbound item during a user-defined period of time based on historical demand data for the inbound item;

applying, using the computer system, the user-defined promotional data to the predicted demand requirements to determine a predicted promotional demand for the inbound item; and

Using the computer system, a number of required instances of the inbound item required to satisfy the order fulfillment requirement in the facility during the user-defined period is determined based on the predicted promotional demand and the productivity of the facility.

12. A method for distributing different types of items commonly ordered together to the same location within an automated warehouse facility, the method comprising:

creating a database of groups of item types that are typically purchased together based on a historical pattern of consumer purchases; and

a recommended storage location for the group of items is determined based on at least one selected from the pending order fulfillment requirements and the predicted requirements.

13. A method for sequencing inbound transport vehicles at an automated warehouse facility, the method comprising:

predicting demand requirements for an inbound item during a user-defined period of time based on historical demand data for the inbound item;

applying the user-defined promotional data to the predicted demand requirements to determine a predicted promotional demand for the inbound item;

determining a shortage in inventory based on a comparison of the predicted promotional demand, the current pending order, and the current inventory in the facility; and

The on-site delivery vehicles at the facility are ranked according to which on-site vehicles contain items determined to be in shortage.